Our blog is shortly describing DCASE2022 task on acoustic scene classification and submitted systems. It is based on the recently published paper in DCASE2022 Workshop, and results of the challenge have been published in the DCASE community website.
Machine learning fairness is a growing field that seeks to cement the abstract principles of "fairness" in machine learning algorithms.
Underspecification and fairness in machine learning (ML) applications have recently become two prominent issues in the ML community. Acoustic scene classification (ASC) applications have so far remained unaffected by this discussion, but are now becoming increasingly used in real-world systems where fairness and reliability are critical aspects.
